Fix mistakes in R files

waternk · Apr 12, 2017 · a73984d · a73984d
1 parent bac5927
commit a73984d
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Showing 2 changed files with 42 additions and 6 deletions.
diff --git a/BPA/Ch.07/7.10.2_Time-dependent_models.R b/BPA/Ch.07/7.10.2_Time-dependent_models.R
@@ -10,10  10,10 @@ set.seed(123)
 ## Read data
 ## The data generation code is in bpa-code.txt, available at
 ## http://www.vogelwarte.ch/de/projekte/publikationen/bpa/complete-code-and-data-files-of-the-book.html
-stan_data <- read_rdump("cjs_mnl_age.data.R")
 stan_data <- read_rdump("cjs_mnl.data.R")
 
 ## Parameters monitored
-params <- c("mean_phijuv", "mean_phiad", "mean_p")
 params <- c("phi", "p", "fit", "fit_new")
 
 ## MCMC settings
 ni <- 2000
@@ -22,12  22,11 @@ nb <- 1000
 nc <- 4
 
 ## Initial values
-inits <- function() list(mean_phijuv = runif(1, 0, 1),
-                         mean_phiad = runif(1, 0, 1),
-                         mean_p = runif(1, 0, 1))
 inits <- function() list(phi= runif(dim(stan_data$marr)[2] - 1, 0, 1),
                          p = runif(dim(stan_data$marr)[2] - 1, 0, 1))
 
 ## Call Stan from R
-cjs_mnl_age  <- stan("cjs_mnl_age.stan",
 cjs_mnl_age  <- stan("cjs_mnl.stan",
                      data = stan_data, init = inits, pars = params,
                      chains = nc, iter = ni, warmup = nb, thin = nt,
                      seed = 1,

diff --git a/BPA/Ch.07/7.10.3_Age-dependent_models.R b/BPA/Ch.07/7.10.3_Age-dependent_models.R
@@ -0,0  1,37 @@
 ## 7. Estimation of survival probabilities using capture-recapture data
 ## 7.10. Fitting the CJS to data in the m-array format: the multinomial likelihood
 ## 7.10.3. Age-dependent models
 
 library(rstan)
 rstan_options(auto_write = TRUE)
 options(mc.cores = parallel::detectCores())
 set.seed(123)
 
 ## Read data
 ## The data generation code is in bpa-code.txt, available at
 ## http://www.vogelwarte.ch/de/projekte/publikationen/bpa/complete-code-and-data-files-of-the-book.html
 stan_data <- read_rdump("cjs_mnl_age.data.R")
 
 ## Parameters monitored
 params <- c("mean_phijuv", "mean_phiad", "mean_p")
 
 ## MCMC settings
 ni <- 2000
 nt <- 1
 nb <- 1000
 nc <- 4
 
 ## Initial values
 inits <- function() list(mean_phijuv = runif(1, 0, 1),
                          mean_phiad = runif(1, 0, 1),
                          mean_p = runif(1, 0, 1))
 
 ## Call Stan from R
 cjs_mnl_age  <- stan("cjs_mnl_age.stan",
                      data = stan_data, init = inits, pars = params,
                      chains = nc, iter = ni, warmup = nb, thin = nt,
                      seed = 1,
                      open_progress = FALSE)
 
 ## Summarize posteriors
 print(cjs_mnl_age, digits = 3)